39 results about "Semantic computing" patented technology

The invention relates to the cross technical field of business intelligence and natural language processing, in particular to an interactive AI report generation method and system based on intelligent semantic driving, and the method comprises the steps: (1) a large language model analyzes user question semantics, calculates the matching degree with a report subject, and dynamically selects a question correction or report generation process; (2) the fuzzy query is converted into a deterministic request based on the domain knowledge base, and semantic ambiguity is eliminated; (3) analyzing field association in combination with database metadata, and generating an executable SQL (Structured Query Language); (4) dynamically rewriting SQL (Structured Query Language) according to user roles, adding permission filtering conditions, executing query and desensitizing sensitive data; (5) analyzing result features, automatically matching a visual form and generating natural language interpretation; and (6) collecting user feedback, and optimizing a semantic model and a query strategy. According to the scheme, the accuracy of natural language query and the adaptive capacity of the system can be remarkably improved, and the security of data access is guaranteed.

The invention provides a multi-source knowledge fusion method, device and equipment based on semantic calculation, and relates to the technical field of data processing.The method comprises the steps that multi-source data are preprocessed, knowledge units are extracted from structured data of a unified format, and the knowledge units are stored in a database; inputting the knowledge units into a target word vector model to obtain target semantic vectors corresponding to the knowledge units; determining a comprehensive similarity between the target semantic vectors, wherein the comprehensive similarity is determined based on a normalized weighted value of a cosine similarity and an Euclidean distance; determining a confidence evaluation value of each knowledge unit based on a confidence evaluation model, wherein the confidence evaluation value of each knowledge unit is used for representing the reliability degree of each knowledge unit; and generating a fused knowledge base according to the comprehensive similarity between the target semantic vectors corresponding to the knowledge units and the confidence evaluation values of the knowledge units. According to the method, the problems of lack of semantic understanding and inaccurate processing in the prior art are solved.

The invention discloses a question query processing method and electronic equipment, and relates to the technical field of data processing, and the method comprises the following steps: obtaining context information from a historical dialogue according to a query question; rewriting the query problem according to the context information to obtain a plurality of rewritten query problems; retrieving each first reference text block and a plurality of reference semantics of any rewritten query problem; calculating a first similarity between each first reference text block and the rewritten query problem; calculating a second similarity between each reference semantic and the rewritten query problem; generating new context information according to the first similarities, the second similarities, the first reference text blocks and the second reference text blocks corresponding to the reference semantics; according to the method, the query question and the new context information are input into the preset language model to obtain the query result, and the context information and the new context information are obtained and used for assisting query of the query question, so that the query result better meets real requirements of a user.

The invention discloses an image description generation system, a training method, a generation method and electronic equipment, and belongs to the technical field of image description. According to the method, visual features of an image are mapped to a visual and language comparable space, after a semantic information sequence is obtained, cross-modal semantic calculation of the semantic information sequence and the visual feature sequence is achieved through a Transform decoder, the middle hidden state of each candidate vocabulary is obtained, and then a corresponding directed acyclic graph is constructed; and after an optimal path is selected from the directed acyclic graph, the optimal path is directly mapped into image text description by a linear classifier. According to the method, visual information of the image and semantic information contained in the image are fully utilized, the sequential relation between words is learned by introducing the directed acyclic graph, the smoothness of description generation is improved, the method has non-autoregressive decoding attributes, and high-quality image text description can be generated at a high speed.

The invention discloses a business demand book recommendation method and device, relates to the technical field of artificial intelligence, can be used in the financial science and technology field, and comprises the steps: employing a fine-grained semantic information extractor to respectively carry out fine-grained semantic extraction on a to-be-matched title and a corresponding label of a business demand book, and contents of stock and the corresponding label of the business demand book, obtaining fine-grained business semantics of the title and fine-grained business semantics of the content; a coarse-grained semantic information extractor is adopted to perform coarse-grained semantic extraction on a to-be-matched title and a corresponding label of the business demand book, and the content of the stock and the corresponding label of the business demand book, and coarse-grained business semantics of the title and coarse-grained business semantics of the content are obtained; according to all extracted business semantics, calculating a matching degree score of the title and the content of each stock; and recommending the content of the stock with the highest matching degree score to a business demand book writer. According to the method and the device, high-adaptability content can be recommended to the title of the target demand book.

The invention provides a behavior verification method and device of an information physical system, electronic equipment and a medium, and the method comprises the steps: for a to-be-verified function of the to-be-verified information physical system, obtaining a mixed operation signal which is generated in the operation process of the system and is related to the to-be-verified function; obtaining a time-sequence point to be verified; calling a pre-defined mixed signal sequential logic formula for formally describing the function to be verified; utilizing Boolean semantics to judge whether the mixed operation signal meets a mixed signal sequential logic formula on a time-sequence point or not; and / or, calculating a robustness value of the mixed signal sequential logic formula on a time-sequence point by using robust semantics so as to quantify the degree of meeting or violating the mixed signal sequential logic formula; and determining whether the to-be-verified function passes verification or not according to the judgment result of the Boolean semantics or the robustness value. Unified processing and verification of the mixed operation signals are realized through the method.

The invention relates to the technical field of data analysis and processing, and discloses a data analysis and processing method based on intelligent AI, which comprises the following steps of: 1, constructing a knowledge graph model, modeling a data entity and a relationship, mapping a knowledge graph to a vector space by adopting a graph embedding method, and constraining a semantic relationship of data by utilizing a first-order predicate logic rule; 2, on the basis of the semantic relation of the knowledge graph, data correction constraints are constructed by means of S5 modal logical reasoning, necessary conditions and possible conditions of data are defined, and correction values of data points under the logical constraints are calculated through Kripke semantics; and step 3, on the basis of the data correction constraint, combining neural logic reasoning and a variational auto-encoder to optimize the data. According to the method, the technical scheme that intelligent map construction is combined with S5 modal logical reasoning is adopted, the data semantic rigorous correction effect is achieved, and compared with an existing traditional data cleaning scheme, the problems that logic constraints are not tight and correction precision is insufficient are solved.

The invention discloses a behavior insight and perception enhancement method and system based on digital twinning, and relates to the technical field of computer data processing and artificial intelligence. The method comprises the following steps: firstly collecting a computer terminal operation behavior log of a user as basic data mapping; performing semantic understanding and feature extraction on the discrete behavior logs by using a large language model as a semantic calculation engine and combining a preset cue word engineering technology, and constructing a digital behavior twin model capable of mapping behavior habits, intentions and psychological states of the user; based on the twinning model, generating a behavior insight report including multiple dimensions such as personal portraits, staged review, target tracking prediction and the like; and finally, by integrating an interactive interface of the visual board and the natural language dialogue ability, the user can visually view and interact with the digitized behavior of the user. According to the method, low-value original behavior data can be converted into high-value semantic intelligence, and the perception depth and the self-optimization capability of a user on a digital behavior mode of the user are remarkably enhanced.

The invention provides a robot positioning method and system based on multi-sensor fusion and a semantic map. The method comprises the steps that a monocular camera is used for recognizing a semantic object, and the direction angle of the semantic object in a camera coordinate system is calculated; the laser radar point cloud is converted to a camera coordinate system, and accurate position information of the object is acquired in combination with semantic direction information; constructing an environment map with semantic annotation as priori knowledge; the current pose is calculated through semantic matching during navigation and compared with a system positioning result, and when the pose error is smaller than a threshold value, it is considered that robot positioning is correct; and otherwise, positioning again and recovering accurate positioning by taking the semantic calculation pose as a reference. The method has the advantages of low hardware cost, high environmental adaptability and the like, the positioning problem caused by dynamic interference and feature deficiency is effectively solved, the positioning precision and robustness of the robot in a complex environment are remarkably improved, and the method can be widely applied to a positioning navigation system of the robot.

The present application discloses a question query processing method and electronic device, which relate to the field of data processing technology, including: obtaining context information from historical conversations according to a query question; rewriting the query question according to the context information to obtain multiple rewritten query questions; retrieving each first reference text block and multiple reference semantics of any rewritten query question; calculating a first similarity between each first reference text block and the rewritten query question; calculating a second similarity between each reference semantic and the rewritten query question; generating new context information based on each first similarity, each second similarity, each first reference text block, and the second reference text block corresponding to each reference semantic; inputting the query question and the new context information into a preset language model to obtain a query result, and using the obtained context information and the new context information to assist in querying the query question, so that the query result better meets the user's real needs.

The invention discloses an LLM-driven semantic association extension and structure completion patent recommendation method and system, and the method comprises the steps: S100, carrying out the concept induction and completion of a discrete patent attribute text based on LLM, so as to generate the background context information of a patent or an enterprise; s200, based on context semantics generated by a large language model, background context correlation between patents and between enterprises is calculated, Top-k most related patents or enterprises are selected according to correlation sorting, a same-field background edge relation is constructed, patent-patent and enterprise-enterprise correlation edges are complemented, and a heterogeneous network structure is obtained; and S300, performing feature propagation and aggregation on the heterogeneous network structure based on a graph convolution model, aggregating high-order heterogeneous neighbor features, optimizing a recommendation relationship in the heterogeneous network structure, and predicting the probability of occurrence of patent recommendation behaviors. According to the method provided by the invention, the accuracy rate is improved by 8.28%, the precision rate is improved by 1.73%, the recall rate is improved by 12.31%, and the F1 score is improved by 6.23%.

The invention discloses a job execution method and device, a storage medium and a program product. The method comprises the steps of obtaining a target job identifier and an initial value of a context environment variable; according to the target job identifier, determining at least one target template unit included in a target job corresponding to the target job identifier and an initial execution sequence of the at least one target template unit; obtaining a target process semantic unit corresponding to each target template unit; and according to the initial value of the context environment variable, the initial execution sequence, the at least one target template unit and the semantic calculation result of the target flow semantic unit corresponding to the target template unit, iteratively determining and executing the actually executed target template unit in each target template unit. The operation execution method is high in flexibility.

The invention discloses an address text desensitization method meeting differential privacy, and belongs to the field of privacy protection and natural language processing. On the basis of a traditional planar Laplacian mechanism, the concept of address semantics is introduced and semantic comparison is performed, so that the privacy-protected address has higher availability. Firstly, for a specific address, the longitude and latitude of the address are obtained by using an address coding service, then the disturbed longitude and latitude are obtained by using a planar Laplacian mechanism, all address information in a certain fixed range is inquired for the disturbed geographic position, and an address information list is obtained; secondly, calculating semantic similarity between addresses in the list and an original address by utilizing a predefined semantic calculation mechanism; and finally, selecting a final address in combination with a measurement local differential privacy (MLDP) mechanism.

The embodiment of the invention discloses a data processing method, device and equipment, and the method comprises the steps: receiving a semantic obtaining request for target data, and the semantic obtaining request comprises semantic coding information and semantic input parameter information; obtaining semantic configuration information corresponding to the target data based on the semantic coding information, and initializing a semantic object logic attribute value corresponding to the target data based on the semantic input parameter information; calling a semantic calculation unit based on the semantic configuration information corresponding to the target data, and performing semantic calculation on the target data through the called semantic calculation unit based on the semantic configuration information corresponding to the target data and the initialized semantic object logic attribute value corresponding to the target data, a corresponding semantic calculation result is obtained; and based on semantic configuration information corresponding to the target data and the semantic calculation result, constructing and outputting semantic information of the target data.

The application belongs to the field of semantic computing and knowledge base construction, and particularly relates to a semantic knowledge base construction system, method and device, aiming to solve the problem that the existing semantic knowledge base construction system based on a data lake cannot describe rules with more semantic connotations, and the existing rule engine does not allow users to set independently, resulting in that the constructed semantic knowledge base cannot be applied across platforms. The system comprises a data acquisition module, a first rule generation module, a second rule generation module, a cost calculation module, a rule optimization module, a rule subnetwork generation and pre-allocation module, a rule subnetwork division module, a semantic feature data extraction module and a semantic knowledge base construction module. The application extracts rules with more connotations, models the semantic rules of users through a structured rule description language, and further realizes the cross-platform application of the semantic knowledge base.

The invention discloses a knowledge graph updating method, device and equipment and a readable storage medium, and is applied to the technical field of knowledge graphs and semantic computation.The knowledge graph updating method comprises the steps that to-be-updated information and a business logic model, a graph structure model and a storage model in a unified defined knowledge graph are obtained; converting the to-be-updated information into first information which can be identified by the business logic model; updating the business logic model based on the first information to obtain an updated business logic model; when it is determined that the updated service logic model is reasonable, the information to be updated is converted into second information and third information which can be recognized by the graph structure model and the storage model, the graph structure model and the storage model are updated based on the second information and the third information, and an updated knowledge graph is obtained. According to the method, objects of all layers of the business model, the graph structure model and the storage model are automatically unified and updated in real time, so that any update can be dynamically perceived and synchronously adjusted, and the update efficiency of the knowledge graph model can be improved.

The application discloses a data query method and device, electronic equipment and readable storage medium. The method comprises the following steps: after receiving at least one semantic query statement, mapping information of a metadata graph atlas ontology is acquired, wherein the mapping information comprises a mapping relationship between a graph attribute class in the metadata graph atlas ontology for describing a data structure of a target data source and configuration file information of a storage file in the target data source; according to the mapping relationship and a graph attribute class corresponding to the semantic query statement, configuration file information corresponding to the semantic query statement is queried; a target storage file corresponding to the configuration file information is extracted from the target data source; the target storage file is converted into a target data set based on the metadata graph atlas ontology; and semantic calculation is performed on the target data set to obtain a query result corresponding to the semantic query statement. The application solves the technical problem that the number of data islands increases rapidly in the prior art, which leads to excessive management workload of data and reduces data management efficiency.

This application discloses a method, system, apparatus, and medium for processing document semantic information. The method involves acquiring an information document to be parsed, parsing the document to obtain all measurable quantity information units within it, mapping each measurable quantity information unit to an RGB channel to obtain a mapped color for each unit, constructing a mapped color image based on the mapped colors of all the measurable quantity information units, and performing corresponding processing tasks based on the mapped color image. This method combines color calculation with semantic calculation of measurable quantity information, avoiding a certain degree of loss of overall semantic information and effectively representing the overall semantic information of measurable quantity information, thus aiding in semantic information processing. This application can be widely applied in the field of document information technology.

This invention relates to the field of business intelligence and natural language processing, specifically an interactive AI report generation method and system based on intelligent semantics. The method includes: (1) analyzing the semantics of user questions using a large language model, calculating the matching degree with the report topic, and dynamically selecting a question correction or report generation process; (2) converting fuzzy queries into deterministic requests based on a domain knowledge base to eliminate semantic ambiguity; (3) parsing field associations using database metadata to generate executable SQL; (4) dynamically rewriting SQL according to user roles, adding permission filtering conditions, executing the query, and desensitizing sensitive data; (5) analyzing result features, automatically matching visualization formats, and generating natural language explanations; and (6) collecting user feedback to optimize the semantic model and query strategy. This solution significantly improves the accuracy of natural language queries and the system's adaptive capabilities, while ensuring the security of data access.

The application discloses a text semantic calculation and cognitive input evaluation method based on conceptual representation. Starting from the perspective of psycholinguistics and based on the language features of educational concepts, the application formally describes two important dimensions of the familiarity and abstractness of educational concepts, quantitatively calculates the attribute values of the familiarity and abstractness of educational concepts, and constructs a two-dimensional attribute model to better understand and apply educational concepts. The constructed "familiarity-abstractness (F-A)" model for educational concepts effectively maps educational concepts into a two-dimensional space. By quantitatively calculating the psychological and linguistic attribute values of educational concepts, online discussion text conceptualization is further realized. With the help of the model, the text semantic complexity of online discussion text can be accurately calculated, so that the cognitive input state and cognitive processing process of learners can be more deeply understood, and the cognitive input level of online discussion text can be further automatically evaluated.

The invention provides a computing power server operation and maintenance auditing method and system based on a block chain and the Internet of Things. The method comprises the steps that physical and logic operation and maintenance behaviors are collected in a unified mode, a structured event chain is constructed, behavior weights are calculated in combination with time, identity and semantics, server state difference analysis is conducted with events as anchor points, and attribution credibility is quantified. And finally, a structured auditing record containing identity, time, state abstract and credibility score is generated, and the structured auditing record is sequentially chained and stored after digital signature, so that a responsibility evidence chain which cannot be tampered and can be verified is formed, and the problems that behaviors and results are disjointed and the evidence chain is incomplete in operation and maintenance auditing are effectively solved. According to the method, cross-layer association of physical and logic behaviors, accurate attribution of operation and maintenance results and long-term credible evidence storage of auditing evidences are realized, and the method is suitable for computing power infrastructure scenes with high safety and compliance requirements.

The present invention relates to the technical field of item recommendation, and specifically relates to an item recommendation method, device, equipment and medium based on multi-modal representation. The present invention first performs alignment encoding processing on text and images to obtain a text semantic encoding matrix and an image semantic encoding matrix, and then predicts the preference degree of a user for each item according to the text semantic encoding matrix, the image semantic encoding matrix and the item representation matrix. Finally, according to the preference degree of the user, the target recommended item is obtained. The alignment in the present invention is to make the corresponding same row in the two matrices of the text semantic encoding matrix and the image semantic encoding matrix point to the same item, so as to effectively represent the same item. Since the alignment can accurately match the text semantics and image semantics corresponding to the same item, subsequent calculation of the preference degree of the user for each item can be performed based on the text semantics and image semantics of the item, thereby improving the recommendation accuracy.

The invention discloses a text semantic calculation and cognitive input evaluation method based on conceptualized representation. According to the method, two important dimensions of the familiarity and the abstraction degree of the education concept are described in a formalized mode from the perspective of psychological linguistics on the basis of the language features of the education concept, the familiarity attribute value and the abstraction degree attribute value of the education concept are calculated in a quantitative mode, and a two-dimensional attribute model is constructed so that the education concept can be better understood and applied. A familiarity-abstraction (F-A) model oriented to the educational concept is constructed, and the educational concept is effectively mapped into a two-dimensional space. By quantitatively calculating psychological language attribute values of education concepts, conceptualization of online discussion texts is further realized. By means of the model, the text semantic complexity of the online discussion text can be accurately calculated, so that the cognitive input state and the cognitive processing process of a learner can be deeply understood, and the cognitive input level of the online discussion text can be further automatically evaluated.

The invention relates to the technical field of edge computing, in particular to a broadcast content dynamic scheduling method and system based on edge computing driving, and the method comprises the steps: sensing the crowd density of each region in real time through deploying a lightweight crowd detection model at an edge end, and constructing a structured region state model as a space basis for judging whether to schedule or not; a structured event intention expression mechanism of a multi-source broadcast task is introduced, the degree of adaptation between the task and the space is calculated in combination with crowd state and task type semantics, and whether a scheduling task is generated or not is screened; a multi-factor task scoring mechanism is constructed, and regional scheduling saturation and resource redundancy suppression items, priority ranking of broadcast tasks and space competition management are introduced; an execution task package is constructed in real time according to a scheduling plan and an equipment state, a judgment function for judging whether a task can be executed and a mode control mechanism are fused, execution actions such as code rate reduction playing, playing delay and task caching are achieved, and it is ensured that broadcast scheduling is reasonable and has high execution force and high robustness.

This invention discloses an automatic construction and dynamic evolution method for domain ontology based on proactive metadata and semantic bridging, belonging to the interdisciplinary fields of knowledge graph construction, semantic computation, and data governance. The method first collects proactive metadata from multiple heterogeneous data sources, extracts semantic features, and vectorizes them. Then, it constructs a cross-data source semantic bridging graph. Based on the bridging graph, it automatically generates domain concept classes, attributes, and hierarchical structures, and optimizes confidence through a manual verification mechanism. This method further supports incremental updates after the addition of new data sources, realizing the dynamic evolution of the domain ontology. Compared with traditional manual construction methods, this invention reduces reliance on manual intervention, improves construction efficiency and semantic consistency, and is suitable for large-scale data governance and knowledge graph construction scenarios.

The application provides a multi-source knowledge fusion method, device and equipment based on semantic calculation, and relates to the technical field of data processing. The method comprises the following steps: preprocessing multi-source data, extracting each knowledge unit from structured data in a unified format, and inputting the knowledge unit into a target word vector model to obtain a target semantic vector corresponding to the knowledge unit; determining the comprehensive similarity between the target semantic vectors, wherein the comprehensive similarity is determined based on a normalized weighted value of cosine similarity and Euclidean distance; determining a confidence evaluation value of each knowledge unit based on a confidence evaluation model, wherein the confidence evaluation value of each knowledge unit is used to represent the reliability of each knowledge unit; and generating a fused knowledge base according to the comprehensive similarity between the target semantic vectors corresponding to each knowledge unit and the confidence evaluation value of each knowledge unit. The application solves the problems of lack of semantic understanding and inaccurate processing in the prior art.

The invention provides a semantic calculation method and device for an authorization policy, a storage medium and a program product, and the method comprises the steps: obtaining a first authorization policy and a second authorization policy; respectively converting the first authorization strategy and the second authorization strategy into a first intermediate presentation layer and a second intermediate presentation layer which conform to a preset grammar structure; the preset grammar structure and grammar structures to which the first authorization strategy and the second authorization strategy belong can be mutually converted; and performing semantic calculation on the first intermediate presentation layer and the second intermediate presentation layer to obtain semantic calculation results of the first authorization strategy and the second authorization strategy. According to the invention, semantic calculation can be performed on different authorization policies, so that conflict detection is performed on the authorization policies according to the semantic calculation result.

The invention relates to the field of information retrieval, in particular to an information consultation intelligent retrieval system and method.The system comprises a cross-table index module, a retrieval feature module, a statement processing module, a granularity retrieval module and a resource allocation module, the cross-table index module is used for constructing an index structure, and the retrieval feature module is used for synthesizing feature vectors; the query module is used for inputting query data, outputting a retrieval basis vector, the statement processing module is used for receiving a consultation text and a projection granularity text, the granularity retrieval module is used for retrieving resources and outputting a retrieval result, and the resource allocation module is used for constructing a vector tree and allocating retrieval resources. According to the method, the retrieval generalization ability is enhanced, the comprehensiveness of the retrieval content is improved, the time complexity is low, maintenance and expansion are convenient, the expenditure of retrieval semantic calculation is reduced, the retrieval efficiency is improved, and the more stable retrieval performance is achieved.

This invention discloses a lightweight method and system for BIM models, specifically relating to the fields of computer-aided design and building information modeling (BIM). The method includes parsing the original BIM model to extract geometric, semantic, and parametric information of components; calculating the comprehensive importance of components based on engineering semantics; dividing non-critical areas into high and low priority categories through clustering; and employing an edge-folding algorithm for differentiated geometric simplification. Simultaneously, it identifies and merges identical components, establishing a geometric template library for reuse; furthermore, it selects core attributes based on the engineering scenario and performs layered compression of geometric, attribute, and index data; finally, it integrates and encapsulates the data into a structured lightweight data package, which is then output after quality assessment and iterative optimization. This invention improves compression ratio while ensuring critical accuracy, intelligently eliminates redundancy, and ensures that the lightweight model possesses high quality and strong engineering applicability.

The embodiment of the specification discloses a data processing method, device and equipment, the method comprises: receiving the semantic acquisition request for the target data, the semantic acquisition request includes semantic encoding information and semantic parameter information; based on the semantic encoding information, the semantic configuration information corresponding to the target data is acquired, and based on the semantic parameter information, the semantic object logical attribute value corresponding to the target data is initialized; based on the semantic configuration information corresponding to the target data, the semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data, the semantic calculation unit is called to perform semantic calculation on the target data, and the corresponding semantic calculation result is obtained; based on the semantic configuration information corresponding to the target data and the semantic calculation result, the semantic information of the target data is constructed and output.